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1. Enforcing fair grid energy access for controllable distributed solar capacity

   https://doi.org/10.1145/3137133.3137147  

   Bashir, Noman; Irwin, David; Shenoy, Prashant; Taneja, Jay (November 2017, ACM International Conference on Systems for Energy-Efficient Built Environments)

   The rapid expansion of intermittent grid-tied solar capacity is making the job of balancing electricity's real-time supply and demand increasingly challenging. To address the problem, recent work proposes mechanisms for actively controlling solar power output to the grid by enabling software to cap it as a fraction of its time-varying maximum output. Utilities can use these mechanisms to dynamically share the grid's solar capacity by controlling the solar output at each site. However, while enforcing an equal fraction of each solar site's time-varying maximum output results in "fair" short-term contributions of solar power, it does not result in "fair" long-term contributions of solar energy. This discrepancy arises from fundamental differences in enforcing "fair" access to the grid to contribute solar energy, compared to analogous fair-sharing in networks and processors. In this paper, we present a centralized and distributed algorithm to enable control of distributed solar capacity that enforces fair grid energy access. We implement our algorithm and evaluate it on synthetic data and real data across 18 solar sites. We show that traditional rate allocation, which enforces equal rates, results in solar sites contributing up to 18.9% less energy than an algorithm that enforces fair grid energy access over a single month. 

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2. Helios: a programmable software-defined solar module

   https://doi.org/10.1145/3276774.3276783  

   Bashir, Noman; Irwin, David; Shenoy, Prashant (November 2018, Proceedings of the 5th Conference on Systems for Built Environments)

   The declining cost and rising penetration of solar energy is poised to fundamentally impact grid operations, as utilities must continuously offset, potentially rapid and increasingly large, power fluctuations from highly distributed and "uncontrollable" solar sites to maintain the instantaneous balance between electricity's supply and demand. Prior work proposes to address the problem by designing various policies that actively control solar power to optimize grid operations. However, these policies implicitly assume the presence of "smart" solar modules capable of regulating solar output based on various algorithms. Unfortunately, implementing such algorithms is currently not possible, as smart inverters embed only a small number of operating modes and are not programmable. To address the problem, this paper presents the design and implementation of a software-defined solar module, called Helios. Helios exposes a high-level programmatic interface to a DC-DC power optimizer, which enables software to remotely control a solar module's power output in real time between zero and its current maximum, as dictated by the Sun's position and weather. Unlike current smart inverters, Helios focuses on enabling direct programmatic control of real solar power capable of implementing a wide range of control policies, rather than a few highly-specific operating modes. We evaluate Helios' performance, including its latency, energy usage, and flexibility. For the latter, we implement and evaluate a wide range of solar control algorithms both in the lab, using a solar emulator and programmable load, and outdoors. 

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3. Virtual energy storage through decentralized load control with quality of service bounds

   https://doi.org/10.23919/ACC.2017.7963040  

   Brooks, Jonathan; Barooah, Prabir (May 2017, American Control Conference)

   null (Ed.)

   We propose a decentralized algorithm to help reduce demand-supply imbalance in a power grid by varying the demand from loads, just like charging and discharging a battery. The algorithm ensures strict bounds on the consumers' quality of service (QoS) by constraining the bandwidth of demand variation. A model-predictive-control formulation is adopted to compute local decisions at the loads. The algorithm is decentralized in the sense that loads do not communicate with one another. Instead, loads coordinate using local measurements of the grid frequency, which provide information about global demand-supply imbalance. It is envisioned that consumers will be recruited through long-term contracts, aided by the QoS guarantees provided by the proposed scheme. Simulation results show that loads are able to reduce frequency deviations while maintaining QoS constraints and that the performance of the algorithm scales well with the number of loads. Closed-loop stability is established under some assumptions. 

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4. On the Feasibility, Cost, and Carbon Emissions of Grid Defection

   https://doi.org/10.1109/SmartGridComm.2019.8909691  

   Bansal, Akansha Singh; Irwin, David (October 2019, IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm))

   Distributed solar generation is rising rapidly due to a continuing decline in the cost of solar modules. Nearly all of this solar generation feeds into the grid, since battery based energy storage is expensive to install and maintain. Unfortunately, accommodating unlimited intermittent solar power is challenging, since the grid must continuously balance supply and demand. Thus, governments and public utility commissions are increasingly limiting grid connections of new solar installations. These limitations are likely to become more restrictive over time in many areas as solar disrupts the utility business model. Thus, to employ solar without restrictions, users may increasingly need to defect from the grid. Unfortunately, batteries alone are unlikely to become cost-efficient at enabling grid defection for the foreseeable future. To address the problem, we explore using a mixture of solar, batteries, and a whole-home natural gas generator to shift users partially or entirely off the electric grid. We assess the feasibility and compare the cost and carbon emissions of such an approach with using grid power, as well as existing “net metered” solar installations. Our results show that the approach is trending towards cost-competitive based on current prices, reduces carbon emissions relative to using grid power, and enables users to install solar without restriction. 

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5. Recent Advances in Cyberattack Detection and Mitigation Techniques for Renewable Photovoltaic Distributed Energy CPS

   Jessica Whitaker and Danda B. Rawat (June 2023, Computing Conference)

   Cyberattacks targeted to the energy cyber-physical system (ECPS), also known as the smart grid, could interrupt the electricity supply with major ramifications. Attackers identify and exploit any vulnerable portion of the energy power grid, including the inverters with solar-powered photovoltaic (PV) panels. PV presents unique challenges as electricity consumers have also become providers of solar energy for utilities. As mandates require increased PV penetration across the world for positive environmental impacts, increased cyberattacks targeted at PV systems impact reliability and efficiency within the ECPS. The new technologies continuously being introduced to manage the ECPS and ensure bi-directional communications and energy flow between components also lead to more attack surfaces, system vulnerabilities, and heightened malicious attacks. Data integrity attacks are increasing within PV systems. In this paper, we present a survey of different methods that are proposed and explored for identifying and preventing cyberattacks targeted at PV systems. The attack detection methods include voltage control, data diodes, and voltage measurement algorithms. Furthermore, we present blockchain, cyber switching, and other attack mitigation techniques for PV systems. 

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